About the Team
You'll be joining our Retail Technology AI & Data team, the engine behind Zurich's Retail Claims, Pricing and Underwriting (UW) solutions. This is where data, AI and cloud engineering directly shape how we protect our customers every day.
Responsibilities
•Design and build end-to-end Data and AI solutions: architect scalable, secure and observable data pipelines and services, from ingestion to production, following modern SDLC best practices.
•Own data processing at scale in the cloud: implement high-performance ETL/ELT in AWS or Azure, leveraging Spark / Databricks (batch and real-time) with a strong focus on data quality, lineage and reliability.
•Industrialise ML & AI with solid MLOps and CI/CD: build and maintain CI/CD pipelines (Azure DevOps, Jenkins, etc.) for data platforms and ML products, enabling automated testing, deployment and monitoring across environments.
•Develop and operate cloud-native microservices: design and implement microservices and APIs that expose data and AI capabilities, deployed in secure, resilient cloud environments.
•Define MLOps industrialisation strategies: shape how models are productionised — versioning, feature stores, monitoring, drift detection, and model lifecycle management — in close collaboration with Data Science and Architecture teams.
•Bridge business and technology: translate Claims, Pricing and UW requirements into robust technical architectures, influencing design decisions and ensuring solutions are both feasible and valuable.
•Build AI-powered products with LLMs: design and implement AI products based on LLMs, including prompt engineering, fine-tuning, retrieval-augmented generation (RAG) and agentic workflows that augment how business teams work.
Requirements
•Core technologies: Advanced Python, Databricks, AWS, Docker, Kubernetes or similar, Git or similar, LLMs, Spark, Azure DevOps or Jenkins.
•Python: 5–10 years building production-grade data and backend solutions.
•Cloud Engineering: 5 years on AWS or Azure, preferably in data-intensive environments.
•Databricks: 5–10 years experience working with this cloud-based data and AI platform.
•CI/CD & DevOps: 5 years designing multi-cloud pipelines and automated deployments (infrastructure, data and ML).
•Microservices: 5 years designing, implementing and operating distributed services and APIs.
•Agentic AI / LLMs: 2 years integrating OpenAI, Anthropic, AI agents or MCP-based services into real applications.
•Backend Engineering: 2 years building and operating APIs and end-to-end backend services.
Nice to Have
•Previous experience in insurance, financial services or other highly regulated industries.
•Exposure to Claims, Pricing or Underwriting domains and their data.
Benefits
•Competitive salary and a yearly bonus.
•Flexible working model to support work-life balance.
•Option to work abroad up to 25 days yearly.
•Over 300 euros to set up your home office, plus additional monthly home office allowance.
•Wide range of internal and external trainings, including English, German and Spanish classes depending on needs.
•Ticket restaurant and Health Insurance, with flexibility to exchange it for other benefits.
•Life and accident insurance.
•Collective Life retirement plan.
•2000 referral bonus for bringing in talented people.
•Special banking and insurance conditions plus exclusive employee discounts.
•Functional diversity benefits.
•Stock options and mortgage benefits.
